Showing papers by "University of Memphis published in 2020"
TL;DR: Analysis of compositional and contextual factors associated with drug overdose deaths rates in the US reveals a consistently strong association between compositional mental health factors and census tract-level death rates from drug overdose.
Abstract: Background: In 2017, the US Department of Health and Human Services declared the Opioid epidemic a public health emergency. In the US, emergency rooms treat more than 1,000 people each day for drug overdose, and 115 of them die. This study examines compositional and contextual factors associated with drug overdose deaths rates in the US. Methods: Local spatial autocorrelation statistics were used to estimate hot spot areas to identify census tracts with high risk of drug overdose death. Logistic regressions investigated the relationship between drug overdose death rates and various compositional and contextual variables across census tracks. Results: The adjusted logistic model shows that compositional variables: depression (OR = 2.47 [2.37-2.58]), poor mental health (OR = 1.71 [1.63-1.79]), median age 1.41 (1.36-1.47) and the percentage of people with a high school diploma (OR = 1.30 [1.24-1.35]) were positively associated with the rate of drug overdose deaths. On the other hand, contextual variables: the percentage having health insurance (OR = 0.66 [0.64-0.69]), the Theil's H index (OR = 0.69 [0.66-0.71]), population density (OR = 0.80 [0.77-0.84]), poverty (OR = 0.90 [0.86-0.95]), and median household income (OR = 0.91[0.86-0.96]) were negatively associated with drug overdose deaths. Discussion: The analysis reveals a consistently strong association between compositional mental health factors and census tract-level death rates from drug overdose.
524 citations
TL;DR: VerifyNet is proposed, the first privacy-preserving and verifiable federated learning framework that claims that it is impossible that an adversary can deceive users by forging Proof, unless it can solve the NP-hard problem adopted in the model.
Abstract: As an emerging training model with neural networks, federated learning has received widespread attention due to its ability to update parameters without collecting users’ raw data. However, since adversaries can track and derive participants’ privacy from the shared gradients, federated learning is still exposed to various security and privacy threats. In this paper, we consider two major issues in the training process over deep neural networks (DNNs): 1) how to protect user’s privacy (i.e., local gradients) in the training process and 2) how to verify the integrity (or correctness) of the aggregated results returned from the server. To solve the above problems, several approaches focusing on secure or privacy-preserving federated learning have been proposed and applied in diverse scenarios. However, it is still an open problem enabling clients to verify whether the cloud server is operating correctly, while guaranteeing user’s privacy in the training process. In this paper, we propose VerifyNet, the first privacy-preserving and verifiable federated learning framework. In specific, we first propose a double-masking protocol to guarantee the confidentiality of users’ local gradients during the federated learning. Then, the cloud server is required to provide the Proof about the correctness of its aggregated results to each user. We claim that it is impossible that an adversary can deceive users by forging Proof , unless it can solve the NP-hard problem adopted in our model. In addition, VerifyNet is also supportive of users dropping out during the training process. The extensive experiments conducted on real-world data also demonstrate the practical performance of our proposed scheme.
388 citations
University of Tartu1, American Museum of Natural History2, University of Gothenburg3, Swedish University of Agricultural Sciences4, University of Oslo5, University of Hawaii at Manoa6, University of Copenhagen7, Purdue University8, Academy of Sciences of the Czech Republic9, University of Turin10, Harvard University11, Synlab Group12, Universidad Mayor13, Universidad Santo Tomás14, University of Electronic Science and Technology of China15, University of Warsaw16, Swedish Museum of Natural History17, Mae Fah Luang University18, University of Florida19, Laos Ministry of Agriculture and Forestry20, São Paulo Federal Institute of Education, Science and Technology21, Estonian University of Life Sciences22, Federal University of Pernambuco23, United States Department of Energy24, Del Rosario University25, National Autonomous University of Mexico26, Ghent University27, West Bengal State University28, Beijing Forestry University29, Pontifical Catholic University of Chile30, Chinese Academy of Sciences31, Field Museum of Natural History32, University of Potsdam33, Leibniz Association34, University of Gilan35, University of Alaska Fairbanks36, University of Tokyo37, University of Costa Rica38, Forest Research Institute39, Westmead Hospital40, University of Sydney41, Uppsala University42, Landcare Research43, University of Chittagong44, University of Memphis45, United Arab Emirates University46, Ministry of Land and Resources of the People's Republic of China47, University of Pretoria48, Royal Botanic Gardens49, Ocean University of China50, Guizhou University51, Mie University52, Hokkaido University53
TL;DR: Fungal traits and character database FungalTraits operating at genus and species hypothesis levels is presented in this article, which includes 17 lifestyle related traits of fungal and Stramenopila genera.
Abstract: The cryptic lifestyle of most fungi necessitates molecular identification of the guild in environmental studies. Over the past decades, rapid development and affordability of molecular tools have tremendously improved insights of the fungal diversity in all ecosystems and habitats. Yet, in spite of the progress of molecular methods, knowledge about functional properties of the fungal taxa is vague and interpretation of environmental studies in an ecologically meaningful manner remains challenging. In order to facilitate functional assignments and ecological interpretation of environmental studies we introduce a user friendly traits and character database FungalTraits operating at genus and species hypothesis levels. Combining the information from previous efforts such as FUNGuild and Fun(Fun) together with involvement of expert knowledge, we reannotated 10,210 and 151 fungal and Stramenopila genera, respectively. This resulted in a stand-alone spreadsheet dataset covering 17 lifestyle related traits of fungal and Stramenopila genera, designed for rapid functional assignments of environmental studies. In order to assign the trait states to fungal species hypotheses, the scientific community of experts manually categorised and assigned available trait information to 697,413 fungal ITS sequences. On the basis of those sequences we were able to summarise trait and host information into 92,623 fungal species hypotheses at 1% dissimilarity threshold.
245 citations
TL;DR: Polyvinylpyrrolidone (PVP) is a water-soluble polymer obtained by polymerization of monomer N-vinyl pyrrolide as discussed by the authors, which can be used as a brace component for gene delivery, orthopedic implants, and tissue engineering applications.
190 citations
TL;DR: This review discusses methods utilized for the fabrication and engineering of MNPs, and challenges in the field and potential opportunities for the use ofMNPs toward improving their properties are discussed.
Abstract: There is urgency for the development of nanomaterials that can meet emerging biomedical needs. Magnetic nanoparticles (MNPs) offer high magnetic moments and surface-area-to-volume ratios that make them attractive for hyperthermia therapy of cancer and targeted drug delivery. Additionally, they can function as contrast agents for magnetic resonance imaging (MRI) and can improve the sensitivity of biosensors and diagnostic tools. Recent advancements in nanotechnology have resulted in the realization of the next generation of MNPs suitable for these and other biomedical applications. This review discusses methods utilized for the fabrication and engineering of MNPs. Recent progress in the use of MNPs for hyperthermia therapy, controlling drug release, MRI, and biosensing is also critically reviewed. Finally, challenges in the field and potential opportunities for the use of MNPs toward improving their properties are discussed.
188 citations
Indiana University1, University of Hamburg2, University of Münster3, Baylor College of Medicine4, Columbia University5, University of Washington6, United States Department of Agriculture7, Georgia Institute of Technology8, University of Pennsylvania9, University of Melbourne10, Washington and Lee University11, Lewis & Clark College12, University of Vermont13, California Academy of Sciences14, Wayne State University15, University of Massachusetts Lowell16, Agricultural Research Service17, University of Kassel18, Swiss Institute of Bioinformatics19, Foundation for Research & Technology – Hellas20, École normale supérieure de Lyon21, University of Wisconsin-Madison22, University of Notre Dame23, University of California, Riverside24, Oxford Brookes University25, University of Memphis26, Lawrence Berkeley National Laboratory27, University of Freiburg28, University of Kentucky29, University of Warwick30, University of Cologne31, University of Massachusetts Boston32, University of Göttingen33, North Carolina State University34, Colorado State University35, University of Georgia36, Arkansas State University37, Naturhistorisches Museum38, National Scientific and Technical Research Council39, University of Cincinnati40, University of Rochester41, Hebrew University of Jerusalem42, Max Planck Society43, University of California, Davis44
TL;DR: These analyses demonstrate how large-scale comparative genomics can provide broad new insights into the genotype to phenotype map and generate testable hypotheses about the evolution of animal diversity.
Abstract: Arthropods comprise the largest and most diverse phylum on Earth and play vital roles in nearly every ecosystem. Their diversity stems in part from variations on a conserved body plan, resulting from and recorded in adaptive changes in the genome. Dissection of the genomic record of sequence change enables broad questions regarding genome evolution to be addressed, even across hyper-diverse taxa within arthropods. Using 76 whole genome sequences representing 21 orders spanning more than 500 million years of arthropod evolution, we document changes in gene and protein domain content and provide temporal and phylogenetic context for interpreting these innovations. We identify many novel gene families that arose early in the evolution of arthropods and during the diversification of insects into modern orders. We reveal unexpected variation in patterns of DNA methylation across arthropods and examples of gene family and protein domain evolution coincident with the appearance of notable phenotypic and physiological adaptations such as flight, metamorphosis, sociality, and chemoperception. These analyses demonstrate how large-scale comparative genomics can provide broad new insights into the genotype to phenotype map and generate testable hypotheses about the evolution of animal diversity.
145 citations
TL;DR: Eigen-CAM was found to be robust against classification errors made by fully connected layers in CNNs, does not rely on the backpropagation of gradients, class relevance score, maximum activation locations, or any other form of weighting features, and works with all CNN models without the need to modify layers or retrain models.
Abstract: Deep neural networks are ubiquitous due to the ease of developing models and their influence on other domains. At the heart of this progress is convolutional neural networks (CNNs) that are capable of learning representations or features given a set of data. Making sense of such complex models (i.e., millions of parameters and hundreds of layers) remains challenging for developers as well as the end-users. This is partially due to the lack of tools or interfaces capable of providing interpretability and transparency. A growing body of literature, for example, class activation map (CAM), focuses on making sense of what a model learns from the data or why it behaves poorly in a given task. This paper builds on previous ideas to cope with the increasing demand for interpretable, robust, and transparent models. Our approach provides a simpler and intuitive (or familiar) way of generating CAM. The proposed Eigen-CAM computes and visualizes the principle components of the learned features/representations from the convolutional layers. Empirical studies were performed to compare the Eigen-CAM with the state-of-the-art methods (such as Grad-CAM, Grad-CAM++, CNN-fixations) by evaluating on benchmark datasets such as weakly-supervised localization and localizing objects in the presence of adversarial noise. Eigen-CAM was found to be robust against classification errors made by fully connected layers in CNNs, does not rely on the backpropagation of gradients, class relevance score, maximum activation locations, or any other form of weighting features. In addition, it works with all CNN models without the need to modify layers or retrain models. Empirical results show up to 12% improvement over the best method among the methods compared on weakly supervised object localization.
139 citations
TL;DR: In this article, the effect of powder feedstock, fabrication parameters, and post fabrication treatments on the resulting microstructure, defect characteristics, and surface quality of the fabricated Ti-6Al-4V parts is evaluated.
133 citations
TL;DR: Results of DNA methylation-quantitative trait loci (mQTL) analyses on 32,851 participants reveal that the genetic architecture of DNAm levels is highly polygenic and DNAm exhibits signatures of negative and positive natural selection.
Abstract: Characterizing genetic influences on DNA methylation (DNAm) provides an opportunity to understand mechanisms underpinning gene regulation and disease. Here we describe results of DNA methylation-quantitative trait loci (mQTL) analyses on 32,851 participants, identifying genetic variants associated with DNAm at 420,509 DNAm sites in blood. We present a database of >270,000 independent mQTL of which 8.5% comprise long-range (trans) associations. Identified mQTL associations explain 15-17% of the additive genetic variance of DNAm. We reveal that the genetic architecture of DNAm levels is highly polygenic and DNAm exhibits signatures of negative and positive natural selection. Using shared genetic control between distal DNAm sites we construct networks, identifying 405 discrete genomic communities enriched for genomic annotations and complex traits. Shared genetic factors are associated with both blood DNAm levels and complex diseases but in most cases these associations do not reflect causal relationships from DNAm to trait or vice versa indicating a more complex genotype-phenotype map than has previously been hypothesised.
130 citations
TL;DR: Wang et al. as discussed by the authors built the Remote Sensing Ecological Index (RSEI) based on Landsat data and Tiangong-2 WIS, using multi-source remote sensing data to comprehensively evaluate the coupling and coordination relationship between urbanization and ecological environment with a coupling coordination degree model.
126 citations
TL;DR: In this paper, the powder-process-structure relationships and how powder feedstock, manufacturing, and post-processing conditions can affect the microstructure and defect features that ultimately contribute to the fatigue performance of Ti-6Al-4V parts.
TL;DR: The results indicate that these terms appear to be often interchanged with blurred distinctions, and the focus group proposes the use of two new terms, " vocal demand" and "vocal demand response," in place of the terms "v vocal load" and 'vocal loading.
Abstract: Purpose The purpose of this document is threefold: (a) review the uses of the terms "vocal fatigue," "vocal effort," "vocal load," and "vocal loading" (as found in the literature) in order to track the occurrence and the related evolution of research; (b) present a "linguistically modeled" definition of the same from the review of literature on the terms; and (c) propose conceptualized definitions of the concepts. Method A comprehensive literature search was conducted using PubMed/MEDLINE, Embase, Cochrane Central Register of Controlled Trials, and Scientific Electronic Library Online. Four terms ("vocal fatigue," "vocal effort," "vocal load," and "vocal loading"), as well as possible variants, were included in the search, and their usages were compiled into conceptual definitions. Finally, a focus group of eight experts in the field (current authors) worked together to make conceptual connections and proposed consensus definitions. Results The occurrence and frequency of "vocal load," "vocal loading," "vocal effort," and "vocal fatigue" in the literature are presented, and summary definitions are developed. The results indicate that these terms appear to be often interchanged with blurred distinctions. Therefore, the focus group proposes the use of two new terms, "vocal demand" and "vocal demand response," in place of the terms "vocal load" and "vocal loading." We also propose standardized definitions for all four concepts. Conclusion Through a comprehensive literature search, the terms "vocal fatigue," "vocal effort," "vocal load," and "vocal loading" were explored, new terms were proposed, and standardized definitions were presented. Future work should refine these proposed definitions as research continues to address vocal health concerns.
TL;DR: This review provides an overview of the electrospinning process, its principles, and the application of the resultant electrospun nanofibers for tissue engineering, including skin, blood vessels, nerves, bone, cartilage, and tendon/ligament applications.
TL;DR: In this paper, the authors focused on the role of technology transfer in the European continent (i.e., countries inside and outside the Eurozone) by focusing on environment-related patents and examined the effects of environmental water-related adaptation technology and climate change mitigation patents on real gross domestic product.
TL;DR: In this paper, a detailed analysis of consumer preferences, trust, attitudes, and willingness to pay (WTP) using a representative sample of 483 consumers in Portland was performed, revealing six underlying consumer segments: Direct Shoppers, E-Shopping Lovers, COVID converts, Omnichannel Consumers, e-shopping Skeptics, and Indifferent Consumers.
Abstract: Autonomous delivery robot (ADR) technology for last-mile freight deliveries is a valuable step towards low-carbon logistics. The ongoing COVID-19 pandemic has put a global spotlight on ADRs for contactless package deliveries, and tremendous market interest has been pushing ADR developers to provide large-scale operation in several US cities. The deployment and penetration of ADR technology in this emerging marketplace calls for collection and analysis of consumer preference data on ADRs. This study addresses the need for research on public acceptance of ADRs and offers a detailed analysis of consumer preferences, trust, attitudes, and willingness to pay (WTP) using a representative sample of 483 consumers in Portland. The results reveal six underlying consumer segments: Direct Shoppers, E-Shopping Lovers, COVID Converts, Omnichannel Consumers, E-Shopping Skeptics, and Indifferent Consumers. By identifying the WTP determinants of these latent classes, this study provides actionable guidance for fostering mass adoption of low-carbon deliveries in the last-mile.
15 Jun 2020
TL;DR: It is argued that monocytes, a circulating innate immune cell, are principal players in cytokine storm and associated pathologies in COVID-19, which suggests a potential mechanism underlying increased morbidity and mortality due to SARS-CoV-2 infection in older adults.
Abstract: The ongoing pandemic severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes a disproportionate number of severe cases and deaths in older adults Severe SARS-CoV-2-associated disease (coronavirus disease 2019 (COVID-19)) was declared a pandemic by the World Health Organization in March 2020 and is characterized by cytokine storm, acute respiratory distress syndrome, and in some cases by systemic inflammation-related pathology Currently, our knowledge of the determinants of severe COVID-19 is primarily observational Here, I review emerging evidence to argue that monocytes, a circulating innate immune cell, are principal players in cytokine storm and associated pathologies in COVID-19 I also describe changes in monocyte function and phenotype that are characteristic of both aging and severe COVID-19, which suggests a potential mechanism underlying increased morbidity and mortality due to SARS-CoV-2 infection in older adults The innate immune system is therefore a potentially important target for therapeutic treatment of COVID-19, but experimental studies are needed, and SARS-CoV-2 presents unique challenges for pre-clinical and mechanistic studies in vivo The immediate establishment of colonies of SARS-CoV-2-susceptible animal models for aging studies, as well as strong collaborative efforts in the geroscience community, will be required in order to develop the therapies needed to combat severe COVID-19 in older adult populations
TL;DR: This article presents a review of state-of-the-art traffic monitoring systems focusing on the major functionality–vehicle classification and discusses hardware/software design, deployment experience, and system performance of vehicle classification systems.
Abstract: A traffic monitoring system is an integral part of Intelligent Transportation Systems (ITS). It is one of the critical transportation infrastructures that transportation agencies invest a huge amount of money to collect and analyze the traffic data to better utilize the roadway systems, improve the safety of transportation, and establish future transportation plans. With recent advances in MEMS, machine learning, and wireless communication technologies, numerous innovative traffic monitoring systems have been developed. In this article, we present a review of state-of-the-art traffic monitoring systems focusing on the major functionality-vehicle classification. We organize various vehicle classification systems, examine research issues and technical challenges, and discuss hardware/software design, deployment experience, and system performance of vehicle classification systems. Finally, we discuss a number of critical open problems and future research directions in an aim to provide valuable resources to academia, industry, and government agencies for selecting appropriate technologies for their traffic monitoring applications.
TL;DR: A good understanding of the angiogenic mechanism holds a promise of providing effective treatments for breast cancer progression, thereby enhancing patients' survival, and the undergoing research in the development of angiogenesis-targeting therapies is highlighted.
Abstract: Angiogenesis is a significant event in a wide range of healthy and diseased conditions. This process frequently involves vasodilation and an increase in vascular permeability. Numerous players referred to as angiogenic factors, work in tandem to facilitate the outgrowth of endothelial cells (EC) and the consequent vascularity. Conversely, angiogenic factors could also feature in pathological conditions. Angiogenesis is a critical factor in the development of tumors and metastases in numerous cancers. An increased level of angiogenesis is associated with decreased survival in breast cancer patients. Therefore, a good understanding of the angiogenic mechanism holds a promise of providing effective treatments for breast cancer progression, thereby enhancing patients' survival. Disrupting the initiation and progression of this process by targeting angiogenic factors such as vascular endothelial growth factor (Vegf)-one of the most potent member of the VEGF family- or by targeting transcription factors, such as Hypoxia-Inducible Factors (HIFs) that act as angiogenic regulators, have been considered potential treatment options for several types of cancers. The objective of this review is to highlight the mechanism of angiogenesis in diseases, specifically its role in the progression of malignancy in breast cancer, as well as to highlight the undergoing research in the development of angiogenesis-targeting therapies.
University of Memphis1, University of Grenoble2, Emory University3, University of Colorado Boulder4, Hospital Italiano de Buenos Aires5, University of Barcelona6, University of Aberdeen7, Leiden University8, Mount Sinai Hospital9, University of Texas MD Anderson Cancer Center10, Stanford University11, Penn State Cancer Institute12, Pennsylvania State University13, University of Turin14
TL;DR: Adoption of molecular testing for lung cancer is relatively low across the world; barriers include cost, access, quality, turn-around time, and lack of awareness.
TL;DR: How COVID-19 may impact the physical, psychosocial, and healthcare delivery concerns of cancer survivors is described in a commentary written for the Journal of Cancer Survivorship.
Abstract: The recent COVID-19 pandemic has affected the world and has the potential to disproportionately affect and disrupt the lives of cancer survivors, including those currently in treatment, those who have completed treatment, and those who are now living cancer-free. There are currently over 17 million cancer survivors in the USA [1] and millions more around the world [2, 3]. Much has been published over the past several decades about the late and long-term effects of cancer treatment, alongside both the challenges and potential solutions to help patients navigate the healthcare system in order to receive high-quality survivorship care [4, 5]. To date, a number of organizations have provided the cancer survivorship community (both patients and healthcare providers) recommendations pertaining to COVID-19 (Box 1). Unfortunately, at this time, there is limited evidence regarding the impact of COVID-19 on cancer survivors, particularly those who have completed treatment. As the pandemic continues to evolve and scientific evidence emerges, more directed recommendations and guidelines will follow. As editors of the Journal of Cancer Survivorship, the only international peer-reviewed publication dedicated to expanding and disseminating knowledge pertaining directly to this patient population, we wrote this commentary to describe how COVID-19 may impact the physical, psychosocial, and healthcare delivery concerns of cancer survivors. We hope that this information may be helpful in addressing the needs of cancer survivors at the present time and frame the issues that will warrant attention in the future.
TL;DR: In this paper, the authors used images from Landsat5 Thematic Mapper (TM) in 2007 and Landsat8 operational land imager (OLI) in 2013 and 2016 to extract indicators such as greenness, wetness, heat, and dryness that reflect the ecological environment quality of arid area.
TL;DR: The primary objectives were to identify current published research in electronic health (eHealth) and mobile health (mHealth) interventions for youth undergoing cancer treatment and child, adolescent, and young adult survivors of childhood cancer and critically appraise the current scientific evidence on their effectiveness and efficacy.
Abstract: Objectives The primary objectives were to (a) identify current published research in electronic health (eHealth) and mobile health (mHealth) interventions for youth undergoing cancer treatment and child, adolescent, and young adult survivors of childhood cancer and (b) critically appraise the current scientific evidence on their effectiveness and efficacy. As an exploratory aim, we identified pediatric cancer patients' and survivors' perceptions, attitudes, and concerns related to eHealth and mHealth interventions. Methods A comprehensive search of the literature was performed to identify peer-reviewed journal articles that included the use of mHealth and eHealth interventions among youth receiving active cancer treatment and survivors of childhood cancer through the age range of childhood to young adulthood (mean age 21 years or younger at the time of diagnosis; mean age 39 years or younger at the time of intervention). The search was conducted via six electronic databases: PubMed, CINAHL, EMBASE, PsycINFO, IEEEXplore and the Cochrane Library. Results Of the 1879 potential records examined, 21 met criteria for inclusion for a total of 1506 participants. Of the investigations included, 13 were randomized controlled trials, and eight were nonrandomized studies. Findings demonstrated feasibility as well as acceptability with these approaches. Evidence of efficacy for interventions targeting emotional distress, health behaviors, health outcomes, and neurocognitive functioning was mixed. Conclusions Given the growing evidence of efficacy, coupled with increasing access to digital technologies, eHealth and mHealth may serve an important role in improving mental and physical health outcomes of youth undergoing cancer treatment and child, adolescent, and young adult survivors of childhood cancer.
TL;DR: Robust arsenate sequestration occurred generating As-safe water (As <0.01 mg/L), despite the presence of competing ions, and stoichiometric precipitation of iron-arsenate complexes triggered by iron dissolution was established.
Karolinska Institutet1, International Agency for Research on Cancer2, University of Bristol3, University Medical Center Groningen4, Wageningen University and Research Centre5, Boston Children's Hospital6, University of California, San Francisco7, University of Southern California8, University of Paris9, Imperial College London10, University of Hasselt11, Centre Hospitalier Universitaire de Sherbrooke12, Erasmus University Rotterdam13, Dartmouth College14, Cranfield University15, University of Memphis16, University of Oulu17, Max Planck Society18, Harvard University19, Curtin University20, University of Western Australia21, University of California, Berkeley22, Academy for Urban School Leadership23, Katholieke Universiteit Leuven24, Université de Sherbrooke25, University of Southern Denmark26, Pompeu Fabra University27, Michigan State University28, National Institutes of Health29, Norwegian Institute of Public Health30, University of Turku31, University of Helsinki32, Columbia University33, Brigham and Women's Hospital34, University of Copenhagen35, University of Southampton36, University of Oxford37, University of Melbourne38, Emory University39, Paris Descartes University40, Oslo University Hospital41, University of Montpellier42, Charité43, Swiss Tropical and Public Health Institute44, University of Basel45, Karolinska University Hospital46, Science for Life Laboratory47
TL;DR: In this article, a meta-analysis of Illumina's HumanMethylation450-array associations between gestational age and cord blood DNA methylation in 3648 newborns from 17 cohorts without common pregnancy complications, induced delivery or caesarean section was performed.
Abstract: Preterm birth and shorter duration of pregnancy are associated with increased morbidity in neonatal and later life. As the epigenome is known to have an important role during fetal development, we investigated associations between gestational age and blood DNA methylation in children. We performed meta-analysis of Illumina’s HumanMethylation450-array associations between gestational age and cord blood DNA methylation in 3648 newborns from 17 cohorts without common pregnancy complications, induced delivery or caesarean section. We also explored associations of gestational age with DNA methylation measured at 4–18 years in additional pediatric cohorts. Follow-up analyses of DNA methylation and gene expression correlations were performed in cord blood. DNA methylation profiles were also explored in tissues relevant for gestational age health effects: fetal brain and lung. We identified 8899 CpGs in cord blood that were associated with gestational age (range 27–42 weeks), at Bonferroni significance, P < 1.06 × 10− 7, of which 3343 were novel. These were annotated to 4966 genes. After restricting findings to at least three significant adjacent CpGs, we identified 1276 CpGs annotated to 325 genes. Results were generally consistent when analyses were restricted to term births. Cord blood findings tended not to persist into childhood and adolescence. Pathway analyses identified enrichment for biological processes critical to embryonic development. Follow-up of identified genes showed correlations between gestational age and DNA methylation levels in fetal brain and lung tissue, as well as correlation with expression levels. We identified numerous CpGs differentially methylated in relation to gestational age at birth that appear to reflect fetal developmental processes across tissues. These findings may contribute to understanding mechanisms linking gestational age to health effects.
TL;DR: In this paper, a triphase hybrid, multifunctional, magnetically recoverable, sorptive, photocatalytic and degradative, adsorbent (MOF-MBC) was used both to remove and catalyze the photodegradation of Rhodamine B (Rh B) with or without Cr6+ present.
Abstract: MIL-53-Fe metal–organic framework (MOF) was grown using the terephthalic acid linker and FeCl3 into an already prepared, high surface area, magnetic, Douglas fir biochar/Fe3O4 (MBC) adsorbent hybrid. This resulting triphase hybrid, multifunctional, magnetically recoverable, sorptive, photocatalytic and degradative, adsorbent (MOF–MBC) was used both to remove and catalyze the photodegradation of Rhodamine B (Rh B) with or without Cr6+ present. Rh B is a widely used colorant in textile, printing and tanning industries that is also associated with deleterious health effects. Batch aqueous sorption studies were performed at various pHs, Rh B concentrations and temperatures in-order to determine the optimum adsorption pH, kinetics, thermodynamics and sorption capacity. This adsorption followed pseudo-2nd-order kinetics and exhibited a Rh B Langmuir adsorption capacity of ~ 55 mg/g at pH 6, 200 rpm agitation and 25 °C. This MOF–MBC hybrid was characterized by SEM, TEM, EDS, XRD, FT-IR, TGA, BET, Elemental Analysis and XPS. Deethylated and carboxylic compounds were identified as photodegradation intermediates. Electrostatic and π–π stacking interactions are thought to play a significant role in Rh B sorption. Hexavalent chromium (Cr6+) and Rh B often co-exist in tannery and printing waste water. Cr6+ can trigger the photo-degradation of Rh B into CO2 and H2O in the presence of both MIL-53-Fe MOF and MOF–MBC. Hence, adsorbent stripping regeneration can be minimized in real world applications. The biochar phase, aids to disperse the MOF, to minimize particle aggregation, to provide extra stability to the MOF, and serves as secondary adsorption site for heavy metal, oxy anion and organic contaminants. Large biochar particles allow reasonable flow through column beds while supporting other nanophases, which would cause large pressure drops when used alone.
TL;DR: The results from this pilot study in metabolically healthy, active young men suggest that TRF can improve markers of cardiometabolic health.
TL;DR: A common garden experiment with 16S rRNA gene amplicon and shotgun metagenomic sequencing is used to study the drivers of microbiome diversity and composition in three genotypes of the model legume Medicago truncatula grown in two native soil communities, demonstrating strong host filtering effects.
Abstract: Understanding the genetic and environmental factors that structure plant microbiomes is necessary for leveraging these interactions to address critical needs in agriculture, conservation, and sustainability. Legumes, which form root nodule symbioses with nitrogen-fixing rhizobia, have served as model plants for understanding the genetics and evolution of beneficial plant-microbe interactions for decades, and thus have added value as models of plant-microbiome interactions. Here we use a common garden experiment with 16S rRNA gene amplicon and shotgun metagenomic sequencing to study the drivers of microbiome diversity and composition in three genotypes of the model legume Medicago truncatula grown in two native soil communities. Bacterial diversity decreased between external (rhizosphere) and internal plant compartments (root endosphere, nodule endosphere, and leaf endosphere). Community composition was shaped by strong compartment × soil origin and compartment × plant genotype interactions, driven by significant soil origin effects in the rhizosphere and significant plant genotype effects in the root endosphere. Nevertheless, all compartments were dominated by Ensifer, the genus of rhizobia that forms root nodule symbiosis with M. truncatula, and additional shotgun metagenomic sequencing suggests that the nodulating Ensifer were not genetically distinguishable from those elsewhere in the plant. We also identify a handful of OTUs that are common in nodule tissues, which are likely colonized from the root endosphere. Our results demonstrate strong host filtering effects, with rhizospheres driven by soil origin and internal plant compartments driven by host genetics, and identify several key nodule-inhabiting taxa that coexist with rhizobia in the native range. Our results set the stage for future functional genetic experiments aimed at expanding our pairwise understanding of legume-rhizobium symbiosis toward a more mechanistic understanding of plant microbiomes.
18 May 2020
TL;DR: This editorial builds on existing research about computational thinking to discuss it as a multi-faceted theoretical nature and presents computational thinking, as a model of thinking, that is important not only in computer science and mathematics, but also in other disciplines of STEM and integrated STEM education broadly.
Abstract: Computational thinking is widely recognized as important, not only to those interested in computer science and mathematics but also to every student in the twenty-first century. However, the concept of computational thinking is arguably complex; the term itself can easily lead to direct connection with "computing" or "computer" in a restricted sense. In this editorial, we build on existing research about computational thinking to discuss it as a multi-faceted theoretical nature. We further present computational thinking, as a model of thinking, that is important not only in computer science and mathematics, but also in other disciplines of STEM and integrated STEM education broadly.
Max Planck Society1, Tel Aviv University2, Leiden University3, University of Alaska Anchorage4, Academia Sinica5, Liverpool John Moores University6, University of Memphis7, Astrophysics Research Institute8, Diego Portales University9, Peking University10, Universidade Federal do Rio Grande do Sul11, Universidade Federal de Santa Maria12, Durham University13, University of Maryland, College Park14
TL;DR: In this article, the electron densities and their impact on the outflow masses and rates were measured in the central few hundred parsecs of 11 local luminous active galaxies.
Abstract: We report on the determination of electron densities, and their impact on the outflow masses and rates, measured in the central few hundred parsecs of 11 local luminous active galaxies. We show that the peak of the integrated line emission in the active galactic nuclei (AGN) is significantly offset from the systemic velocity as traced by the stellar absorption features, indicating that the profiles are dominated by outflow. In contrast, matched inactive galaxies are characterized by a systemic peak and weaker outflow wing. We present three independent estimates of the electron density in these AGN, discussing the merits of the different methods. The electron density derived from the [S II] doublet is significantly lower than that found with a method developed in the last decade using auroral and transauroral lines, as well as a recently introduced method based on the ionization parameter. The reason is that, for gas photoionized by an AGN, much of the [S II] emission arises in an extended partially ionized zone where the implicit assumption that the electron density traces the hydrogen density is invalid. We propose ways to deal with this situation and we derive the associated outflow rates for ionized gas, which are in the range 0.001–0.5 M⊙ yr−1 for our AGN sample. We compare these outflow rates to the relation between ˙M out and LAGN in the literature, and argue that it may need to be modified and rescaled towards lower mass outflow rates.